The ability to down-regulate leaf maximum net photosynthetic capacity (Amax) and dark respiration rate (Rdark) in response to shading is thought to be an important adaptation of trees to the wide range of light environments that they are exposed to across space and time. A simple, general rule that accurately described this down-regulation would improve carbon cycle models and enhance our understanding of how forest successional diversity is maintained. In this paper, we investigated the light response of Amax and Rdark for saplings of six temperate forest tree species in New Jersey, USA, and formulated a simple model of down-regulation that could be incorporated into carbon cycle models. We found that full-sun values of Amax and Rdark differed significantly among species, but the rate of down-regulation (proportional decrease in Amax or Rdark relative to the full-sun value) in response to shade was not significantly species- or taxon-specific. Shade leaves of sun-grown plants appear to follow the same pattern of down-regulation in response to shade as leaves of shadegrown plants. Given the light level above a leaf and one species-specific number (either the full-sun Amax or full-sun Rdark), we provide a formula that can accurately predict the leaf’s Amax and Rdark. We further show that most of the down regulation of per unit area Rdark and Amax is caused by reductions in leaf mass per unit area (LMA): as light decreases, leaves get thinner, while per unit mass Amax and Rdark remain approximately constant.

Efforts to test and improve terrestrial biosphere models (TBMs) using a variety of data sources have become increasingly common. Yet, geographically extensive forest inventories have been under-exploited in previous model-data fusion efforts. Inventory observations of forest growth, mortality, and biomass integrate processes across a range of timescales, including slow timescale processes such as species turnover, that are likely to have important effects on ecosystem responses to environmental variation. However, the large number (thousands) of inventory plots precludes detailed measurements at each location, so that uncertainty in climate, soil properties, and other environmental drivers may be large. Errors in driver variables, if ignored, introduce bias into model-data fusion. We estimated errors in climate and soil drivers at U.S. Forest Inventory and Analysis (FIA) plots, and we explored the effects of these errors on model-data fusion with the Geophysical Fluid Dynamics Laboratory LM3V dynamic global vegetation model. When driver errors were ignored or assumed small at FIA plots, responses of biomass production in LM3V to precipitation and soil available water capacity appeared steeper than the corresponding responses estimated from FIA data. These differences became nonsignificant if driver errors at FIA plots were assumed to be large. Ignoring driver errors when optimizing LM3V parameter values yielded estimates for fine-root allocation that were larger than biometric estimates, which is consistent with the expected direction of bias. To explore whether complications posed by driver errors could be circumvented by relying on intensive study sites where driver errors are small, we performed a power analysis. To accurately quantify the response of biomass production to spatial variation in mean annual precipitation within the eastern United States would require at least 40 intensive study sites, which is larger than the number of sites typically available for individual biomes in existing plot networks. Driver errors may be accommodated by several existing model-data fusion approaches, including hierarchical Bayesian methods and ensemble filtering methods; however, these methods are computationally expensive. We propose a new approach, in which the TBM functional response is fit directly to the driver-error-corrected functional response estimated from data, rather than to the raw observations.

The dependence of forest productivity and community composition on rainfall is the result of complex interactions at multiple scales, from the physiology of carbon gain and water loss to competition among individuals and species. In an effort to understand the role of these multiscale interactions in the dependence of forest structure on rainfall, we build a tractable model of individual plant competition for water and light. With game-theoretic analyses, we predict the dominant plant allocation strategy, forest productivity, and carbon storage. We find that the amount and timing of rainfall are critical to forest structure. Comparing two forests that differ only in the total time plants spend in water saturation, the model predicts that the wetter forest has fewer fine roots, more leaves, and more woody biomass than the drier forest. In contrast, if two forests differ only in the amount of water available during water limitation, the model predicts that the wetter forest has more fine roots than the drier forest and equivalent leaves and woody biomass. The difference in these responses to increases in water availability has significant implications for potential carbon sinks with rising atmospheric CO2. We predict that enhanced productivity from increased leaf-level water-use efficiency during water limitation will be allocated to fine roots if plants respond competitively, producing only a small and short-lived carbon sink.

A well-documented pattern in the fossil record is a long-term decline in the origination rate of new taxa after diversity rebounds from a mass extinction. The mechanisms for this pattern remain elusive. In this article, we investigate the macroevolutionary predictions of an individual-based birth-death model (BDI model) where speciation and extinction rates emerge from population dynamics. We start with the simplest neutral model in which every individual has the same per capita rates of birth, death, and speciation. Although the prediction of the simplest neutral model agrees qualitatively with the fossil pattern, the predicted decline in per-species speciation rates is too fast to explain the long-term trend in fossil data. We thus consider models with variation among species in per capita rates of speciation and a suite of alternative assumptions about the heritability of speciation rate. The results show that interspecific variation in per capita speciation rate can induce differences among species in their ability to resist extinction because a low speciation rate confers a small but important demographic advantage. As a consequence, the model predicts an appropriately slow temporal decline in speciation rates, which provides a mechanistic explanation for the fossil pattern.

Neutral models of species diversity predict patterns of abundance
for communities in which all individuals are ecologically equivalent.
These models were originally developed for Panamanian
trees and successfully reproduce observed distributions of abundance. Neutral models also make macroevolutionary predictions that have rarely been evaluated or tested. Here we show that neutral models predict a humped or flat relationship between
species age and population size. In contrast, ages and abundances
of tree species in the Panamanian Canal watershed are found to be
positively correlated, which falsifies the models. Speciation rates
vary among phylogenetic lineages and are partially heritable from
mother to daughter species. Variable speciation rates in an otherwise neutral model lead to a demographic advantage for species with low speciation rate. This demographic advantage results in a positive correlation between species age and abundance, as found in the Panamanian tropical forest community.

Alvarez, Ramón A., Stephen W. Pacala, James J. Winebrake, W. Chameides, and Steven P. Hamburg, 2012: Greater focus needed on methane leakage from natural gas infrastructure. Proceedings of the National Academy of Sciences of the United States of America, doi:10.1073/pnas.1202407109[ Abstract ]

Natural gas is seen by many as the future of American energy: a fuel that can provide energy independence and reduce greenhouse gas emissions in the process. However, there has also been confusion
about the climate implications of increased use of natural gas for electric power and transportation. We propose and illustrate the use of technology warming potentials as a robust and transparent way to compare the cumulative radiative forcing created by
alternative technologies fueled by natural gas and oil or coal by using the best available estimates of greenhouse gas emissions from each fuel cycle (i.e., production, transportation and use). We find that a shift to compressed natural gas vehicles from gasoline or diesel vehicles leads to greater radiative forcing of the climate for 80 or 280 yr, respectively, before beginning to produce benefits. Compressed natural gas vehicles could produce climate benefits on all time frames if the well-to-wheels CH4 leakage were capped at a level 4570% below current estimates. By contrast, using natural gas instead of coal for electric power plants can reduce radiative forcing immediately, and reducing CH4 losses from the production and transportation of natural gas would produce even greater benefits. There is a need for the natural gas industry and science community to help obtain better emissions data and for increased efforts to reduce methane leakage in order to minimize the climate footprint of natural gas.

1. We present a model to quantify tropical forest structure and explain variance in dynamic rates
(growth and mortality) that is computationally simple and can be applied to landscape-scale forest
inventory and, potentially, remote sensing-derived data.
2. The model is a modification of the perfect plasticity approximation (PPA) based on tree allometry,
tree locations and sizes. The model quantifies crown area index (CAI) (number of crowns per
unit ground area) and assigns trees to crown layers, which determines the expected number of
crowns above each tree and thus its light environment.
3. The structural model, parameterized and tested for the Barro Colorado Island, Panama 50-ha forest dynamics plot using data from forest inventories and stereo aerial photographs, reproduces most canopy and understorey structural and dynamic properties. The PPA model worked as well or better than a computationally intensive, spatially explicit model. A single allometry for all trees worked equally well as functional group or species allometries. Models of growth and mortality were always improved by adding crown layers as defined by the PPA model.
4. The mean CAI of the 50-ha plot was 3.1 with low variance. The observed variance was lower
than when tree locations were randomized, which drastically lowered the variance in tree density
per plot, indicating that there are regulating forces towards a small range of crown area indices.
5. Synthesis. A number of simplifying characteristics in structure were uncovered with the PPA
structural model applied to a tropical forest: species allometries were not needed despite the high
species diversity in the forest; the model worked on a range of plot sizes; and the variance in CAI was surprisingly low, suggesting regulatory mechanisms. The PPA structural model can be used to develop a fully dynamic simulation model for tropical forests. The ability of the simulation model to predict temporal changes in landscape patterns of biomass, dynamic rates, and species and/or functional group composition will provide validation for the partitioning of dynamic rates by crown layers in the PPA structural model.

The timing and length of burning seasons in different parts of the world depend on climate, land–cover characteristics, and human activities. In this study, global burned area estimates are used in conjunction with global gridded distributions of agricultural land-cover types (defined as the sum of cropland and pasture area) to separate the seasonality of agricultural burning practices from that of non-agricultural fire. The results presented in this study show that agricultural and non-agricultural land experience broadly different fire seasonality patterns that are not always linked to climate conditions. We highlight these differences on a regional basis, examining variations in both agricultural land cover and associated cultural practices to help explain our results. While we discuss two land-cover categories, the methods can be generalized to derive seasonality for any number of land uses or cover types. This will be useful as global fire models evolve to be fully interactive with land-use and land–cover change in the next generation of Earth system models.

Nutrient limitation to net primary production (NPP) displays a diversity of patterns as ecosystems develop over a range of timescales. For example, some ecosystems transition from N limitation on young soils to P limitation on geologically old soils, whereas others appear to remain N limited. Under what conditions should N limitation and P limitation prevail? When do transitions between N and P limitation occur? We analyzed transient dynamics of multiple timescales in an ecosystem model to investigate these questions. Post-disturbance dynamics in our model are controlled by a cascade of rates, from plant uptake (very fast) to litter turnover (fast) to plant mortality (intermediate) to plant-unavailable nutrient loss (slow) to weathering (very slow). Young ecosystems are N limited when symbiotic N fixation (SNF) is constrained and P weathering inputs are high relative to atmospheric N deposition and plant N:P demand, but P limited under opposite conditions. In the absence of SNF, N limitation is likely to worsen through succession (decades to centuries) because P is mineralized faster than N. Over long timescales (centuries and longer) this preferential P mineralization increases the N:P ratio of soil organic matter, leading to greater losses of plant-unavailable N versus P relative to plant N:P demand. These loss dynamics favor N limitation on older soils despite the rising organic matter N:P ratio. However, weathering depletion favors P limitation on older soils when continual P inputs (e.g., dust deposition) are low, so nutrient limitation at the terminal equilibrium depends on the balance of these input and loss effects. If NPP switches from N to P limitation over long time periods, the transition time depends most strongly on the P weathering rate. At all timescales SNF has the capacity to overcome N limitation, so nutrient limitation depends critically on limits to SNF.

A central challenge in community ecology is to
predict patterns of biodiversity with mechanistic models. The neutral model of biodiversity is a simple model that appears to provide parsimonious and accurate predictions of biodiversity patterns in some ecosystems, even though it ignores processes such as species interactions and niche structure. In a recent paper, we used analytical techniques
to reveal why the mean predictions of the neutral model are robust to niche structure in high diversity but not lowdiversity ecosystems. In the present paper, we explore this phenomenon further by generating stochastic simulated data from a spatially implicit hybrid niche-neutral model across different speciation rates. We compare the resulting patterns of species richness and abundance with the patterns expected from a pure neutral and a pure niche model. As the speciation rate in the hybrid model increases, we observe a surprisingly rapid transition from an ecosystem in which diversity is almost entirely
governed by niche structure to one in which diversity is
statistically indistinguishable from that of the neutral
model. Because the transition is rapid, one prediction of our abstract model is that high-diversity ecosystems such as tropical forests can be approximated by one simple model-the neutral model-whereas low-diversity ecosystems such as temperate forests can be approximated by another simple model-the niche model. Ecosystems that require the hybrid model are predicted to be rare, occurring only over a narrow range of speciation rates.

We present a model that scales from the physiological
and structural traits of individual trees competing for light and nitrogen
across a gradient of soil nitrogen to their community-level
consequences. The model predicts the most competitive (i.e., the
evolutionarily stable strategy [ESS]) allocations to foliage, wood, and
fine roots for canopy and understory stages of trees growing in oldgrowth
forests. The ESS allocations, revealed as analytical functions
of commonly measured physiological parameters, depend not on
simple root-shoot relations but rather on diminishing returns of
carbon investment that ensure any alternate strategy will underperform
an ESS in monoculture because of the competitive environment
that the ESS creates. As such, ESS allocations do not maximize
nitrogen-limited growth rates in monoculture, highlighting the underappreciated
idea that the most competitive strategy is not necessarily
the "best," but rather that which creates conditions in which
all others are "worse." Data from 152 stands support the model’s
surprising prediction that the dominant structural trade-off is between
fine roots and wood, not foliage, suggesting the "root-shoot" trade-off is more precisely a "root-stem" trade-off for long-lived trees.
Assuming other resources are abundant, the model predicts that
forests are limited by both nitrogen and light, or nearly so.

"Mass effects," in which "sink populations" of
locally inferior competitors are maintained by dispersal from "source populations" elsewhere in the landscape, are thought to play an important role in maintaining plant diversity. However, due to the complexity of most quasirealistic forest models, there is little theoretical understanding of the strength of mass effects in forests. Here, we develop a
metacommunity version of a mathematically and computationally tractable height-structured forest model, the Perfect Plasticity Approximation, to quantify the strength of mass effects (i.e., the degree of mixing of locally dominant and subordinate species) in heterogeneous landscapes comprising different patch types (e.g., soil types). For realistic levels of
inter-patch dispersal, mass effects are weak at equilibrium (i.e., in the absence of disturbance), even in some cases where differences in growth, mortality, and fecundity rates between locally dominant and subordinate species are too small to be reliably detected from field data. However, patch-scale
transient dynamics are slow following catastrophic disturbance (in which post-disturbance initial abundances are determined exclusively by immigration) so that at any given time, subordinate species are present in appreciable numbers
in most patches. Less severe disturbance regimes, in which some seeds or individuals survive the disturbance, should result in faster transient dynamics (i.e., faster approach to the low-diversity equilibrium). Our results suggest that in order
for mass effects to play an important role in tree coexistence, niche differences must be strong enough to prevent neutral drift, yet too weak to be reliably detected from field data.

The terrestrial carbon sink has been large in recent decades, but its size and location remain uncertain. Using forest inventory data and long-term ecosystem carbon studies, we estimate a total forest sink of 2.4 ± 0.4 petagrams of carbon per year (Pg C year -1) globally for 1990 to 2007. We also estimate a source of 1.3 ± 0.7 Pg C year -1 from tropical land-use change, consisting of a gross tropical deforestation emission of 2.9 ± 0.5 Pg C year -1 partially compensated by a carbon sink in tropical forest regrowth of 1.6 ± 0.5 Pg C year -1. Together, the fluxes comprise a net global forest sink of 1.1 ± 0.8 Pg C year -1, with tropical estimates having the largest uncertainties. Our total forest sink estimate is equivalent in magnitude to the terrestrial sink deduced from fossil fuel emissions and land-use change sources minus ocean and atmospheric sinks.

Chisholm, Ryan A., and Stephen W. Pacala, 2010: Niche and neutral models predict asymptotically equivalent species abundance distributions in high-diversity ecological communities. Proceedings of the National Academy of Sciences of the United States of America, 107(36), doi:10.1073/pnas.1009387107[ Abstract ]

Afundamental challenge inecology is tounderstandthemechanisms
that govern patterns of relative species abundance. Previous numerical
simulations have suggested that complex niche-structured
models produce species abundance distributions (SADs) that are
qualitatively similar to those of very simple neutral models that
ignore differences between species. However, in the absence of an
analytical treatment of niche models, one cannot tell whether the
two classes of model produce the same patterns via similar or
different mechanisms. We present an analytical proof that, in the
limit as diversity becomes large, a strong niche model give rises to
exactly the same asymptotic form of SAD as the neutral model, and
we verify the analytical predictions for a Panamanian tropical forest
data set. Our results strongly suggest that neutral processes drive
patterns of relative species abundance in high-diversity ecological
communities, even when strong niche structure exists. However,
neutral theory cannot explain what generates high diversity in the
first place, and it may not be valid in low-diversity communities. Our
results also confirm that neutral theory cannot be used to infer an
absence of niche structure or to explain ecosystem function.

Geographically extensive forest inventories, such as the USDA Forest Service's Forest Inventory and Analysis (FIA) program, contain millions of individual tree growth and mortality records that could be used to develop broad-scale models of forest dynamics. A limitation of inventory data, however, is that individual-level measurements of light (L) and other environmental factors are typically absent. Thus, inventory data alone cannot be used to parameterize mechanistic models of forest dynamics in which individual performance depends on light, water, nutrients, etc. To overcome this limitation, we developed methods to estimate species-specific parameters (θG) relating sapling growth (G) to L using data sets in which G, but not L, is observed for each sapling. Our approach involves: (1) using calibration data that we collected in both eastern and western North America to quantify the probability that saplings receive different amounts of light, conditional on covariates x that can be obtained from inventory data (e.g., sapling crown class and neighborhood crowding); and (2) combining these probability distributions with observed G and x to estimate θG using Bayesian computational methods. Here, we present a test case using a data set in which G, L, and x were observed for saplings of nine species. This test data set allowed us to compare estimates of θG obtained from the standard approach (where G and L are observed for each sapling) to our method (where G and x, but not L, are observed). For all species, estimates of θG obtained from analyses with and without observed L were similar. This suggests that our approach should be useful for estimating light-dependent growth functions from inventory data that lack direct measurements of L. Our approach could be extended to estimate parameters relating sapling mortality to L from inventory data, as well as to deal with uncertainty in other resources (e.g., water or nutrients) or environmental factors (e.g., temperature).

We show here an updated estimate of the net land
carbon sink (NLS) as a function of time from 1960 to 2007
calculated from the difference between fossil fuel emissions,
the observed atmospheric growth rate, and the ocean uptake
obtained by recent ocean model simulations forced with reanalysis
wind stress and heat and water fluxes. Except for interannual
variability, the net land carbon sink appears to have
been relatively constant at a mean value of −0.27 PgC yr−1
between 1960 and 1988, at which time it increased abruptly
by −0.88 (−0.77 to −1.04) PgC yr−1 to a new relatively
constant mean of −1.15 PgC yr−1 between 1989 and 2003/7
(the sign convention is negative out of the atmosphere). This
result is detectable at the 99% level using a t-test. The land
use source (LU) is relatively constant over this entire time
interval. While the LU estimate is highly uncertain, this does
imply that most of the change in the net land carbon sink
must be due to an abrupt increase in the land sink, LS = NLS
– LU, in response to some as yet unknown combination of
biogeochemical and climate forcing. A regional synthesis
and assessment of the land carbon sources and sinks over
the post 1988/1989 period reveals broad agreement that the
Northern Hemisphere land is a major sink of atmospheric
CO2, but there remain major discrepancies with regard to the
sign and magnitude of the net flux to and from tropical land.

We present a framework for allocating a global carbon reduction target among nations, in
which the concept of ‘‘common but differentiated responsibilities’’ refers to the emissions of
individuals instead of nations. We use the income distribution of a country to estimate how
its fossil fuel CO2 emissions are distributed among its citizens, from which we build up a
global CO2 distribution. We then propose a simple rule to derive a universal cap on global
individual emissions and find corresponding limits on national aggregate emissions from
this cap. All of the world’s high CO2 emitting
individuals are treated the same, regardless of
where they live. Any future global emission goal (target and time frame) can be converted
into national reduction targets, which are determined by ‘‘Business as Usual’’ projections of
national carbon emissions and incountry
income distributions. For example, reducing
projected global emissions in 2030 by 13 GtCO2 would require the engagement of 1.13 billion
high emitters, roughly equally distributed in 4 regions: the U.S., the OECD minus the U.S.,
China, and the nonOECD
minus China. We also modify our methodology to place a floor on
emissions of the world’s lowest CO2 emitters and demonstrate that climate mitigation and
alleviation of extreme poverty are largely decoupled.

Global anthropogenic changes in carbon (C) and nitrogen (N) cycles call for modeling
tools that are able to address and quantify essential interactions between N, C, and
climate in terrestrial ecosystems. Here, we introduce a prognostic N cycle within the
Princeton-GFDL LM3V land model. The model captures mechanisms essential for N
cycling and their feedbacks on C cycling: N limitation of plant productivity, the N
dependence of C decomposition and stabilization in soils, removal of available N by
competing sinks, ecosystem losses that include dissolved organic and volatile N, and
ecosystem inputs through biological N fixation.
Our model captures many essential characteristics of C-N interactions, and is capable of
broadly recreating spatial and temporal variations in N and C dynamics. The introduced
N dynamics improves the model’s short term NPP response to step changes in CO2.
Consistent with theories of successional dynamics, we find that physical disturbance
induces strong C-N feedbacks, caused by intermittent N loss and subsequent N limitation.
In contrast, C-N interactions are weak when the coupled model system approaches
equilibrium. Thus, at steady state many simulated features of the carbon cycle, such as
primary productivity and carbon inventories are similar to simulations that do not include
C-N feedbacks.

A variety of mechanisms have been identified that may result in late-successional declines in forest biomass, including synchronous mortality of even-aged early-successional cohorts, increased susceptibility of mature forests to wind or insect damage, and, in some systems, reduced stature of late-successional species. We used data from the United States (US) Forest Service’s Forest Inventory and Analysis (FIA) program, and a literature database on old-growth biomass, to quantify late-successional biomass trajectories in different US forest types. Our results suggest that late-successional biomass declines are rare in US forests. Thus, in most cases, there is no conflict between maximizing carbon storage in forest biomass and protecting or restoring old-growth forests.

Predictions of forest succession, diversity and function require an
understanding of how species differ in their growth, allocation patterns and
susceptibility to mortality. These processes in turn are affected by allometric
constraints and the physiological state of the tree, both of which are coupled to
the tree’s labile carbon status. Ultimately, insight into the hidden labile pools and
the processes affecting the allocation of labile carbon to storage, maintenance
and growth will improve our ability to predict tree growth, mortality and forest
dynamics. We developed the ‘Allometrically Constrained Growth and Carbon
Allocation’ (ACGCA) model that explicitly couples tree growth, mortality,
allometries and labile carbon. This coupling results in (1) a semi-mechanistic
basis for predicting tree death, (2) an allocation scheme that simultaneously
satisfies allometric relationships and physiology- based carbon dynamics and (3)
a range of physiological states that are consistent with tree behavior (e.g.,
healthy, static, shrinking, recovering, recovered and dead). We present the
ACGCA model and illustrate aspects of its behavior by conducting simulations
under different forest gap dynamics scenarios and with parameter values
obtained for two ecologically dissimilar species: loblolly pine (Pinus taeda L.) and
red maple (Acer rubrum L.). The model reproduces growth and mortality
patterns of these species that are consistent with their shade-tolerance and
succession status. The ACGCA framework provides an alternative, and
potentially improved, approach for predicting tree growth, mortality and forest
dynamics. Keywords: Acer rubrum, carbon allocation, carbon reserves, carbon
storage, growth model, labile carbon, loblolly pine, Pinus taeda, red maple,
retranslocation, shade-tolerance, succession, tree mortality.

We show here a new estimate of the variability and long-term trends in the net land
carbon sink from 1960 onwards calculated from the difference between fossil fuel
emissions, the observed atmospheric growth rate, and the ocean uptake obtained by
5 recent ocean model simulations forced with reanalysis wind stress and heat and water
fluxes. The net land carbon sink appears to have increased by −0.88 (−0.77 to
−1.04) PgCyr−1 after 1988/1989 from a relatively constant mean of −0.27 PgCyr−1
before then to −1.15 PgCyr−1 thereafter (the sign convention is negative out of the
atmosphere). This result is significant at the 1% critical level. The increase in net land
10 uptake is partially compensated by a reduction in the expected oceanic uptake, which
we estimate from model simulations as about 0.35 (0.26 to 0.49) PgCyr−1. This implies
that the atmospheric growth rate must have decreased by about −0.53 (−0.51
to −0.55) PgCyr−1 (equivalent to −0.25 ppm yr−1) below what would have been projected
if the ocean uptake had continued to grow at the rate expected from a constant
15 climate model and if the net land uptake had continued at its pre-1988/1989 level. A
regional synthesis and assessment of the land carbon sources and sinks over the post
1988/1989 period reveals broad agreement that the northern hemisphere land is a
major sink of atmospheric CO2, but there remain major discrepancies with regard to
the sign and magnitude of the net flux to and from tropical land.

We have developed a dynamic land model (LM3V) able to simulate ecosystem
dynamics and exchanges of water, energy, and CO2 between land and atmosphere. LM3V
is specifically designed to address the consequences of land use and land management
changes including cropland and pasture dynamics, shifting cultivation, logging, fire,
and resulting patterns of secondary regrowth. Here we analyze the behavior of LM3V,
forced with the output from the Geophysical Fluid Dynamics Laboratory (GFDL)
atmospheric model AM2, observed precipitation data, and four historic scenarios of
land use change for 1700–2000. Our analysis suggests a net terrestrial carbon source
due to land use activities from 1.1 to 1.3 GtC/a during the 1990s, where the range is due
to the difference in the historic cropland distribution. This magnitude is substantially
smaller than previous estimates from other models, largely due to our estimates of a
secondary vegetation sink of 0.35 to 0.6 GtC/a in the 1990s and decelerating agricultural
land clearing since the 1960s. For the 1990s, our estimates for the pastures’ carbon
flux vary from a source of 0.37 to a sink of 0.15 GtC/a, and for the croplands our model
shows a carbon source of 0.6 to 0.9 GtC/a. Our process-based model suggests a smaller
net deforestation source than earlier bookkeeping models because it accounts for
decelerated net conversion of primary forest to agriculture and for stronger secondary
vegetation regrowth in tropical regions. The overall uncertainty is likely to be higher
than the range reported here because of uncertainty in the biomass recovery under
changing ambient conditions, including atmospheric CO2 concentration, nutrients
availability, and climate.

Spacecraft launched to Mars can retain viable terrestrial microorganisms on board that may survive the interplanetary transit. Such biota might compromise the search for life beyond Earth if capable of propagating on Mars. The current study explored the survivability of Psychrobacter cryohalolentis K5, a psychrotolerant microorganism obtained from a Siberian permafrost cryopeg, under simulated martian surface conditions of high ultraviolet irradiation, high desiccation, low temperature, and low atmospheric pressure. First, a desiccation experiment compared the survival of P. cryohalolentis cells embedded, or not embedded, within a medium/salt matrix (MSM) maintained at 25°C for 24 h within a laminar flow hood. Results indicate that the presence of the MSM enhanced survival of the bacterial cells by 1 to 3 orders of magnitude. Second, tests were conducted in a Mars Simulation Chamber to determine the UV tolerance of the microorganism. No viable vegetative cells of P. cryohalolentis were detected after 8 h of exposure to Mars-normal conditions of 4.55 W/m2 UVC irradiation (200–280 nm), −12.5°C, 7.1 mbar, and a Mars gas mix composed of CO2 (95.3%), N2 (2.7%), Ar (1.6%), O2 (0.2%), and H2O (0.03%). Third, an experiment was conducted within the Mars chamber in which total atmospheric opacities were simulated at ô = 0.1 (dust-free CO2 atmosphere at 7.1 mbar), 0.5 (normal clear sky with 0.4 = dust opacity and 0.1 = CO2-only opacity), and 3.5 (global dust storm) to determine the survivability of P. cryohalolentis to partially shielded UVC radiation. The survivability of the bacterium increased with the level of UVC attenuation, though population levels still declined several orders of magnitude compared to UVC-absent controls over an 8 h exposure period.

Exploiting multiple feedstocks, under new
policies and accounting rules, to balance
biofuel production, food security, and
greenhouse-gas reduction.
Dramatic improvements in policy and technology are needed to meet global demand for both food and biofuel feedstocks.

Energy is at the core of some of the greatest environmental and geopolitical challenges of our time. Cheap and plentiful energy – deemed necessary for our current standard of living – can at the moment only be supported by oil and coal, which pollutes the air, changes the climate, and, in the case of oil and gas, comes from unstable regions. Besides stimulating less polluting energy sources, it is important to improve the overall energy efficiency of the economy through technological, behavioural and other changes. For that, one needs to understand how and why energy use has changed in the past. This paper contributes to that.

The perfect-plasticity approximation (PPA) is an analytically tractable
model of forest dynamics, defined in terms of parameters for
individual trees, including allometry, growth, and mortality. We
estimated these parameters for the eight most common species on
each of four soil types in the US Lake states (Michigan, Wisconsin,
and Minnesota) by using short-term (<15-year) inventory data
from individual trees. We implemented 100-year PPA simulations
given these parameters and compared these predictions to chronosequences
of stand development. Predictions for the timing and
magnitude of basal area dynamics and ecological succession on
each soil were accurate, and predictions for the diameter distribution
of 100-year-old stands were correct in form and slope. For a
given species, the PPA provides analytical metrics for early-successional
performance (H20, height of a 20-year-old open-grown tree)
and late-successional performance (Z*, equilibrium canopy height
in monoculture). These metrics predicted which species were early
or late successional on each soil type. Decomposing Z*, showed that
(i) succession is driven both by superior understory performance
and superior canopy performance of late-successional species, and
(ii) performance differences primarily reflect differences in mortality
rather than growth. The predicted late-successional dominants
matched chronosequences on xeromesic (Quercus rubra) and
mesic (codominance by Acer rubrum and Acer saccharum) soil. On
hydromesic and hydric soils, the literature reports that the current
dominant species in old stands (Thuja occidentalis) is now failing to
regenerate. Consistent with this, the PPA predicted that, on these
soils, stands are now succeeding to dominance by other latesuccessional
species (e.g., Fraxinus nigra, A. rubrum).

Dynamic global vegetation models (DGVMs) have shown that forest dynamics could dramatically alter
the response of the global climate system to increased atmospheric carbon dioxide over the next
century. But there is little agreement between different DGVMs, making forest dynamics one of the
greatest sources of uncertainty in predicting future climate. DGVM predictions could be strengthened by
integrating the ecological realities of biodiversity and height-structured competition for light, facilitated
by recent advances in the mathematics of forest modeling, ecological understanding of diverse
forest communities, and the availability of forest inventory data.

Individual-based forest simulators, such as TASS and SORTIE, are spatial
stochastic processes that predict properties of populations and communities by simulating the
fate of every plant throughout its life cycle. Although they are used for forest management and
are able to predict dynamics of real forests, they are also analytically intractable, which limits
their usefulness to basic scientists. We have developed a new spatial individual-based forest
model that includes a perfect plasticity formulation for crown shape. Its structure allows us to
derive an accurate approximation for the individual-based model that predicts mean densities
and size structures using the same parameter values and functional forms, and also it is
analytically tractable. The approximation is represented by a system of von Foerster partial
differential equations coupled with an integral equation that we call the perfect plasticity
approximation (PPA). We have derived a series of analytical results including equilibrium
abundances for trees of different crown shapes, stability conditions, transient behaviors, such
as the constant yield law and self-thinning exponents, and two species coexistence conditions.

Boreal regions are an important component of the global carbon cycle because they
host large stocks of aboveground and belowground carbon. Since boreal forest evolution is
closely related to fire regimes, shifts in climate are likely to induce changes in
ecosystems, potentially leading to a large release of carbon and other trace gases to the
atmosphere. Prediction of the effect of this potential climate feedback on the Earth system
is therefore important and requires the modeling of fire as a climate driven process in
dynamic global vegetation models (DGVMs). Here, we develop a new data-based
prognostic model, for use in DGVMs, to estimate monthly burned area from four climate
(precipitation, temperature, soil water content and relative humidity) and one humanrelated
(road density) predictors for boreal forest. The burned area model is a function of
current climatic conditions and is thus responsive to climate change. Model parameters are
estimated using a Markov Chain Monte Carlo method applied to on ground observations
from the Canadian Large Fire Database. The model is validated against independent
observations from three boreal regions: Canada, Alaska and Siberia. Provided realistic
climate predictors, the model is able to reproduce the seasonality, intensity and interannual
variability of burned area, as well as the location of fire events. In particular, the
model simulates well the timing of burning events, with two thirds of the events predicted
for the correct month and almost all the rest being predicted 1 month before or after the
observed event. The predicted annual burned area is in the range of various current
estimates. The estimated annual relative error (standard deviation) is twelve percent in a
grid cell, which makes the model suitable to study quantitatively the evolution of burned
area with climate.

We use a two-species model of plant competition to explore the effect of intraspecific
variation on community dynamics. The competitive ability (“performance”) of each individual is
assigned by an independent random draw from a species-specific probability distribution. If the
density of individuals competing for open space is high (e.g., because fecundity is high), species with
high maximum (or large variance in) performance are favored, while if density is low, species with
high typical (e.g., mean) performance are favored. If there is an interspecific mean-variance
performance trade-off, stable coexistence can occur across a limited range of intermediate densities,
but the stabilizing effect of this trade-off appears to be weak. In the absence of this trade-off, one
species is superior. In this case, intraspecific variation can blur interspecific differences (i.e., shift the
dynamics toward what would be expected in the neutral case), but the strength of this effect
diminishes as competitor density increases. If density is sufficiently high, the inferior species is driven
to extinction just as rapidly as in the case where there is no overlap in performance between species.
Intraspecific variation can facilitate coexistence, but this may be relatively unimportant in maintaining
diversity in most real communities.

North America is currently a net source of carbon dioxide to the atmosphere, contributing to the global
buildup of greenhouse gases in the atmosphere and associated changes in the Earth’s climate. In 2003, North
America emitted nearly two billion metric tons of carbon to the atmosphere as carbon dioxide. North
America’s fossil-fuel emissions in 2003 (1856 million metric tons of carbon ± 10% with 95% certainty) were
27% of global emissions. Approximately 85% of those emissions were from the United States, 9% from
Canada, and 6% from Mexico. The combustion of fossil fuels for commercial energy (primarily electricity) is
the single largest contributor, accounting for approximately 42% of North American fossil emissions in 2003.
Transportation is the second largest, accounting for 31% of total emissions.
There are also globally important carbon sinks in North America. In 2003, growing vegetation in North
America removed approximately 500 million tons of carbon per year (± 50%) from the atmosphere and
stored it as plant material and soil organic matter. This land sink is equivalent to approximately 30% of the
fossil-fuel emissions from North America. The imbalance between the fossil-fuel source and the sink on land
is a net release to the atmosphere of 1350 million metric tons of carbon per year (± 25%).
Approximately 50% of North America’s terrestrial sink is due to the regrowth of forests in the United States
on former agricultural land that was last cultivated decades ago, and on timberland recovering from harvest.
Other sinks are relatively small and not well quantified with uncertainties of 100% or more. The future of the
North American terrestrial sink is also highly uncertain. The contribution of forest regrowth is expected to
decline as the maturing forests grow more slowly and take up less carbon dioxide from the atmosphere. But,
how regrowing forests and other sinks will respond to changes in climate and carbon dioxide concentration
in the atmosphere is highly uncertain.
The large difference between current sources and sinks and the expectation that the difference could become
larger if the growth of fossil-fuel emissions continues and land sinks decline suggest that addressing imbalances
in the North American carbon budget will likely require actions focused on reducing fossil-fuel emissions.
Options to enhance sinks (growing forests or sequestering carbon in agricultural soils) can contribute, but
enhancing sinks alone is likely insufficient to deal with either the current or future imbalance. Options to
reduce emissions include efficiency improvement, fuel switching, and technologies such as carbon capture
and geological storage. Implementing these options will likely require an array of policy instruments at local,
regional, national, and international levels, ranging from the encouragement of voluntary actions to economic
incentives, tradable emissions permits, and regulations. Meeting the demand for information by decision
makers will likely require new modes of research characterized by close collaboration between scientists
and carbon management stakeholders.

Background. Canopy structure, which can be defined as the sum of the sizes, shapes and relative placements of the tree
crowns in a forest stand, is central to all aspects of forest ecology. But there is no accepted method for deriving canopy
structure from the sizes, species and biomechanical properties of the individual trees in a stand. Any such method must
capture the fact that trees are highly plastic in their growth, forming tessellating crown shapes that fill all or most of the
canopy space. Methodology/Principal Findings. We introduce a new, simple and rapidly-implemented model–the Ideal Tree
Distribution, ITD–with tree form (height allometry and crown shape), growth plasticity, and space-filling, at its core. The ITD
predicts the canopy status (in or out of canopy), crown depth, and total and exposed crown area of the trees in a stand, given
their species, sizes and potential crown shapes. We use maximum likelihood methods, in conjunction with data from over
100,000 trees taken from forests across the coterminous US, to estimate ITD model parameters for 250 North American tree
species. With only two free parameters per species–one aggregate parameter to describe crown shape, and one parameter to
set the so-called depth bias–the model captures between-species patterns in average canopy status, crown radius, and crown
depth, and within-species means of these metrics vs stem diameter. The model also predicts much of the variation in these
metrics for a tree of a given species and size, resulting solely from deterministic responses to variation in stand structure.
Conclusions/Significance. This new model, with parameters for US tree species, opens up new possibilities for
understanding and modeling forest dynamics at local and regional scales, and may provide a new way to interpret remote
sensing data of forest canopies, including LIDAR and aerial photography.

To accurately assess the impacts of human land use on the Earth system, information is
needed on the current and historical patterns of land-use activities. Previous global
studies have focused on developing reconstructions of the spatial patterns of agriculture.
Here, we provide the first global gridded estimates of the underlying land conversions
(land-use transitions), wood harvesting, and resulting secondary lands annually, for the
period 1700–2000. Using data-based historical cases, our results suggest that 42–68% of
the land surface was impacted by land-use activities (crop, pasture, wood harvest) during
this period, some multiple times. Secondary land area increased 10–44 X 106km2; about
half of this was forested. Wood harvest and shifting cultivation generated 70–90% of the
secondary land by 2000; permanent abandonment and relocation of agricultural land
accounted for the rest. This study provides important new estimates of globally gridded
land-use activities for studies attempting to assess the consequences of anthropogenic
changes to the Earth’s surface over time.

Recent investigations have shown how chance, long-range dispersal events can allow tree populations to migrate rapidly in response to
changes in climate. However, this apparent solution to Reid’s paradox applies solely within the context of single species models, while the
rapid migration rates seen in pollen records occurred within multispecies communities. Ecologists are therefore presented with a new
challenge: reconciling the macroscopic dynamics of spread seen in the pollen record with the rules and interactions governing plant
community assembly. A case that highlights this issue is the rapid spread of Beech during the Holocene into a landscape already
dominated by a close competitor, Hemlock. In this study, we analyse a simple model of plant community assembly incorporating
competition for space and dispersal dynamics, showing how, even when a species is capable of rapid migration into an empty landscape,
the presence of an ecologically similar competitor causes Reid’s paradox to re-emerge because of the dramatic slowing effect of
competitive interactions on a species’ rate of spread. We then show how the answer to the question of how tree species dispersed rapidly
into occupied landscapes may lie in secondary interactions with host-specific pathogens and parasites. Inclusion of host-specific
pathogens into the simple community assembly model illustrates how tree species undergoing range expansions can temporarily outstrip
specialist predators, giving rise to a transient Jansen–Connell effect, in which the invader acts as temporary ‘super-species’ that spreads
rapidly into communities already occupied by competitors at rates consistent with those observed in the paleo-record.

Humanity can emit only so much carbon dioxide into the atmosphere before
the climate enters a state unknown in recent geologic history and goes haywire.
Climate scientists typically see the risks growing rapidly as CO2 levels approach a
doubling of their pre-18thcentury value.
To make the problem manageable, the required reduction in emissions can be
broken down into “wedges”—an incremental reduction of a size that matches
available technology.

We compile a database of energy uses, energy sources, and carbon dioxide
emissions for the USA for the period 1850-2002. We use a model to extrapolate
the missing observations on energy use by sector. Overall emission intensity rose
between 1850 and 1917, and fell between 1917 and 2002. The leading cause for
the rise in emission intensity was the switch from wood to coal, but population
growth, economic growth, and electrification contributed as well. After 1917,
population growth, economic growth and electrification pushed emissions up
further, and there was no net shift from fossil to non-fossil energy sources. From
1850 to 2002, emissions were reduced by technological and behavioural change
(particularly in transport, manufacturing and households), structural change in
the economy, and a shift from coal to oil and gas. These trends are stronger
than electrification, explaining the fall in emissions relative to GDP.

Intergenerational effects occur when an individual’s actions
affect not only its own survivorship and reproduction but also
those of its offspring and possibly later descendants. In the presence
of intergenerational effects, short-term and long-term measures of
success (such as the expected numbers of surviving offspring and of
farther descendants, respectively) may be in conflict. When such
conflicts occur, life-history theory normally takes long-termmeasures
to predict the outcome of selection. This ignores the fact that, because
traits change in time—through mutation, sex, and recombination—
long-term relations disintegrate. We study this issue with numerical
simulations and analytical models combining intergenerational effects
and evolutionary change. In the models, the parental investment
per offspring, as well as the total reproductive effort, stand for investments
in future generations. The models show that the rate of
evolutionary change determines the level of those investments.
Higher rates of mutation and of sexual as opposed to parthenogenetic
reproduction favor lower parental investment per offspring and lower
total reproductive effort. It follows that the level of investment of
ancestors in descendants responds to the genetic relatedness between
the generations of the lineage, in a manner unaccounted for by
preexisting theory.

We can define a neutral community as one in which all species, and so all individuals, are
equivalent, in the sense that they are interchangeable at all times and under all conditions. In
contrast, we can define a structured community as one in which species are not equivalent, and
species-specified differences affect the population dynamics, and therefore the behaviour of the
community.
This distinction is an important one, because in a neutral community the biodiversity, as
measured by species richness and abundance patterns, has nothing to do with the biogeochemical
functioning of the community (e.g. carbon fixation and nutrient-cycling). In fact, in a truly
neutral community one could eliminate all but one species without affecting the biogeochemical
functioning of the community at all.
In contrast, much of the species-specific variation in biological traits observed in reality has
direct relevance for the functioning of the community. For example, the short-term carbon
uptake of a forest depends on the growth rates of the individual trees, and the long-term carbon
storage depends on adult life-span and wood density, and there is wide species-specific variation
in these traits. In niche-structured communities, the biodiversity and functioning are intimately
linked, and some combination of at least some species is required to maintain the functioning of
the community. In the most highly structured community possible there is no equivalence
between any of the species, which is the so-called “one species one niche” idea so prevalent in
the history of ecology: in such a community, removing just one species has a significant impact
on the dynamics and functioning of the community.
Which of these two pictures of communities – neutral or structured – is nearer to the truth?
Is it “one species one niche” or “all species one niche”? This is the neutral vs structure debate,
and it continues apace because there is good evidence for both sides of the argument.

The effects of three forms of density-dependent regulation were explored in model coral
reef fish populations: top-down (predation), bottom-up (competition for food), and pelagic (non-reefbased
mechanisms) control. We describe the demographic responses of both biomass and numbers of
adult fish, predicting the mean and the variance of temporal fluctuations resulting from stochastic
recruitment of juveniles. We find that top-down control acts by suppressing variability of numbers of
fish, which in turn suppresses the variability of biomass. Bottom-up control has no effect on
fluctuations of numbers of fish, though it strongly reduces fluctuations of biomass. Because fecundity
of fish is directly linked to body mass, the regulation of biomass tightly regulates reproductive output
independently of the number of individuals in the population. Finally, populations under pelagic
control experience bounded fluctuations of biomass and numbers directly proportional to the bounded
fluctuations of recruitment. The demographic signatures predicted from both bottom-up and pelagic
control are consistent with current evidence supporting the recruitment limitation hypothesis in reef fish
ecology. We propose tests to discriminate the dominant mode of density-dependent regulation using
qualitative trends in time series demographic data across environmental clines.

Spatially density-dependent predation is a leading hypothesis describing
mechanisms of population regulation in coral reef fish. However, studies supporting this
hypothesis predominantly have been conducted on small, isolated patch reefs. Here, we
searched for evidence of spatially density-dependent predation on the continuous reefs of
the Netherlands Antilles in a study of a dominant planktivore, the blue chromis (Chromis
cyanea). Across space, we quantified both the patterns of loss from site-attached aggregations
of C. cyanea through time and the behavioral reaction of predators to these aggregations.
Looking across C. cyanea densities, we found that loss from aggregations was
not characteristic of direct density dependence, but instead was commonly inversely related
to density. Individual C. cyanea in larger aggregations were less likely to be lost from the
group than were individuals in smaller aggregations. Thus, the observed density dependence
increased spatial heterogeneity of C. cyanea. Predators showed behaviors that were consistent
with these demographic patterns. Using remote videography, we quantified predator
visitation and strike rates across a range of C. cyanea aggregation sizes. Predators consistently
visited and struck at individuals in C. cyanea aggregations in a pattern that was
strongly inversely density dependent, suggesting that aggregation is an effective means of
minimizing per capita risk of predation for prey reef fish. Differences in spatial distribution
of resources for predators (i.e., prey fish) between continuous and patch reef habitats may
explain the difference between these results and those of previous studies on patch reefs.

The RAMS model was used to explore the possible impacts of a large wind farm in the
Great Plains region on the local meteorology over synoptic timescales under typical
summertime conditions. A wind turbine was approximated as a sink of energy and source
of turbulence. The wind farm was created by assuming an array of such turbines. Results
show that the wind farm significantly slows down the wind at the turbine hub-height
level. Additionally, turbulence generated by rotors create eddies that can enhance vertical
mixing of momentum, heat, and scalars, usually leading to a warming and drying of
the surface air and reduced surface sensible heat flux. This effect is most intense in the
early morning hours when the boundary layer is stably stratified and the hub-height level
wind speed is the strongest due to the nocturnal low-level jet. The impact on
evapotranspiration is small.

Carbon estimates from terrestrial ecosystem models are limited by large
uncertainties in the current state of the land surface. Natural and anthropogenic disturbances
have important and lasting influences on ecosystem structure and fluxes that can be difficult
to detect or assess with conventional methods. In this study, we combined two recent
advances in remote sensing and ecosystem modeling to improve model carbon stock and
flux estimates at a tropical forest study site at La Selva, Costa Rica (10°25' N, 84°00' W).
Airborne lidar remote sensing was used to measure spatial heterogeneity in the vertical
structure of vegetation. The ecosystem demography model (ED) was used to estimate the
consequences of this heterogeneity for regional estimates of carbon stocks and fluxes. Lidar
data provided substantial constraints on model estimates of both carbon stocks and net
carbon fluxes. Lidar-initialized ED estimates of aboveground biomass were within 1.2% of
regression-based approaches, and corresponding model estimates of net carbon fluxes differed
substantially from bracketing alternatives. The results of this study provide a promising
illustration of the power of combining lidar data on vegetation height with a heightstructured
ecosystem model. Extending these analyses to larger scales will require the
development of regional and global lidar data sets, and the continued development and
application of height structured ecosystem models.

Large-scale use of wind power can alter local and global climate by extracting
kinetic energy and altering turbulent transport in the atmospheric boundary layer.
We report climate-model simulations that address the possible climatic impacts of
wind power at regional to global scales by using two general circulation models and
several parameterizations of the interaction of wind turbines with the boundary
layer. We find that very large amounts of wind power can produce nonnegligible
climatic change at continental scales. Although large-scale effects are observed,
wind power has a negligible effect on global-mean surface temperature, and it
would deliver enormous global benefits by reducing emissions of CO2 and air
pollutants. Our results may enable a comparison between the climate impacts due
to wind power and the reduction in climatic impacts achieved by the substitution of
wind for fossil fuels.

We analyze tree growth data from Wisconsin forest inventories completed in 1968, 1983, 1996
and 2002. These show that the rate of forest growth decreased steadily over the period, in contrast
to the increases predicted by CO2 fertilization models. Measured growth rate changed an average
of -0.27% y-1 (95% confidence range: -0.05% to -0.49% y-1), whereas the prediction for CO2
fertilization is 0.16% y-1 (corresponding to a ß of 0.36). The high statistical precision is due both to
large sample sizes and positive correlations among the growth rates from different time periods
within the same plot. Decreased growth occurred in stands of all ages, and so our results are not
caused by age-related declines in growth (although highly significant age-related declines were
also detected).
Data allowing a direct examination of growth rates over several decades are available only for
Wisconsin, but Caspersen et al. (2000) introduced an indirect method for detecting past changes in
growth rate using only two sequential inventories. This method was criticized by Joos et al. (2002),
who claimed that it lacked the statistical power to falsify state-of–the-art ecosystem models of CO2
fertilization. We explain both the sound points and the critical errors in Joos et al.’s argument,
introduce a transparent and analytically tractable version of Caspersen et al.’s method, and check
its ability to detect the decreasing growth rates in the Wisconsin data. The results show that the
indirect method accurately characterizes the past changes that actually occurred, and has sufficient
statistical power to falsify CO2 fertilization models, including the model in Joos et al. (2002).
We discuss the implications of decreasing Wisconsin growth rates, together with other reasons
for skepticism about the future magnitude of CO2 fertilization. In particular, the steep reductions in
fossil fuel emissions required to stabilize atmospheric CO2 at 500 ppm must begin more than a
decade sooner if the predictions of the CO2 fertilization models in the IPCC Third Assessment
(Prentice et al. 2001) are incorrect. The difference between a terrestrial carbon sink that grows
because of CO2 fertilization, and one that shrinks because it is caused by recovery from past land
use, is the difference between the luxury of a substantial delay and the need to act now.

Humanity already possesses the fundamental scientific, technical, and industrial know-how to
solve the carbon and climate problem for the next half-century. A portfolio of technologies now
exists to meet the world’s energy needs over the next 50years and limit atmospheric CO2 to a
trajectory that avoids a doubling of the preindustrial concentration. Every element in this
portfolio has passed beyond the laboratory bench and demonstration project; many are already
implemented somewhere at full industrial scale. Although no element is a credible candidate for
doing the entire job (or even half the job) by itself, the portfolio as a whole is large enough that
not every element has to be used.
The debate in the current literature about stabilizing atmospheric CO2 at less than a doubling of
the preindustrial concentration has led to needless confusion about current options for
mitigation. On one side, the Intergovernmental Panel on Climate Change (IPCC) has claimed
that “technologies that exist in operation or pilot stage today” are sufficient to follow a less-thandoubling
trajectory “over the next hundred years or more” [(1), p. 8]. On the other side, a recent
review in Science asserts that the IPCC claim demonstrates “misperceptions of technological
readiness” and calls for “revolutionary changes” in mitigation technology, such as fusion,
space-based solar electricity, and artificial photosynthesis (2). We agree that fundamental
research is vital to develop the revolutionary mitigation strategies needed in the second half of
this century and beyond. But it is important not to become beguiled by the possibility of
revolutionary technology. Humanity can solve the carbon and climate problem in the first half of
this century simply by scaling up what we already know how to do.
13

Volatile organic compounds (VOCs) emitted by woody vegetation influence global
climate forcing and the formation of tropospheric ozone. We use data from over 250 000
re-surveyed forest plots in the eastern US to estimate emission rates for the two most
important biogenic VOCs (isoprene and monoterpenes) in the 1980s and 1990s, and then
compare these estimates to give a decadal change in emission rate. Over much of the
region, particularly the southeast, we estimate that there were large changes in biogenic
VOC emissions: half of the grid cells (1° X 1°) had decadal changes in emission rate
outside the range -2.3% to +16.8% for isoprene, and outside the range 0.2–17.1% for
monoterpenes. For an average grid cell the estimated decadal change in heatwave
biogenic VOC emissions (usually an increase) was three times greater than the decadal
change in heatwave anthropogenic VOC emissions (usually a decrease, caused by
legislation). Leaf-area increases in forests, caused by anthropogenic disturbance, were
the most important process increasing biogenic VOC emissions. However, in the
southeast, which had the largest estimated changes, there were substantial effects of
ecological succession (which decreased monoterpene emissions and had location-specific
effects on isoprene emissions), harvesting (which decreased monoterpene emissions and
increased isoprene emissions) and plantation management (which increased isoprene
emissions, and decreased monoterpene emissions in some states but increased
monoterpene emissions in others). In any given region, changes in a very few tree
species caused most of the changes in emissions: the rapid changes in the southeast were
caused almost entirely by increases in sweetgum (Liquidambar styraciflua) and a few
pine species. Therefore, in these regions, a more detailed ecological understanding of
just a few species could greatly improve our understanding of the relationship between
natural ecological processes, forest management, and biogenic VOC emissions.

The study of population regulation in reef fish populations is confounded by large
amounts of stochasticity obscuring patterns in the field. We analyze a series of population
models, comparing equilibrial solutions under conditions of top-down and bottom-up
regulation. We also treat patterns of population variance that will be expected as recruitment
variance is propagated through to adult populations. We find that predators affect reef fish
populations by absorbing recruitment variance across space and through time. Food
limitation will instead reduce fluctuations of adult fish biomass through time. Our model
suggests that the study of regulation cannot be conducted through counting fish alone, but
requires measurement of biomass simultaneously. By surveying fish across natural and
human-created clines of recruitment and mortality, we can focus fieldwork on testing
focused predictions of regulation on coral reefs.

The atmosphere’s concentration of carbon
dioxide (CO2) has increased by
more than 30 percent over the last 250
years, largely due to human activity. Two-thirds
of that rise has occurred in the past 50 years.1
Unless there is a change, the world will see
much higher CO2 levels in the future—levels
that are predicted to lead to damaging climate
change. Fortunately, many carbon mitigation
strategies are available to set the world on a new
path, one that leads to a lower rate of CO2 emissions
than is currently expected.
The environmental community is currently
playing a prominent role in the development
of the CO2 policies that will elicit these strategies.
Until a few years ago, the environmental
community was almost exclusively interested
in policies that promote renewable energy,
conservation, and natural sinks. More recently,
it has begun to explore alliances with traditional
energy supply industries on the grounds
that to establish the pace required to achieve
environmental goals, parallel action on many
fronts is required.

If the world is willing to accept a tripling of the pre-industrial atmospheric CO2 concentration, significant carbon mitigation can be delayed for most of the next half century. If the world is to be put on a path to avoid a doubling, however, a monumental mitigation effort needs to start now. To convey the magnitude of the effort, we introduce the “wedge” as the unit of mitigation: a wedge is an activity that creates 1 GtC/y of carbon emission reductions in 2054, relative to a world unconcerned about global carbon emissions. To pursue 500 ppm stabilization, the task for the next 50 years is to achieve about seven wedges by avoiding about 175 billion tons of carbon emissions.

We used the Regional Atmospheric Modeling System (RAMS) model to investigate
the possible impact of land cover change on the July climate of the coterminous United
States over the last 290 years. Vegetation data were estimated using the Ecosystem
Demography model. The observed change in land cover leads to a weak warming along the
Atlantic coast and a strong cooling of more than 1 K over the Midwest and the Great
Plains region. The precipitation signal is weaker and shows some reduction in the Midwest
because of changes in the patterns of large-scale moisture advection.

A variety of models have shown that spatial dynamics and small-scale endogenous heterogeneity
(e.g., forest gaps or local resource depletion zones) can change the rate and outcome of competition in
communities of plants or other sessile organisms. However, the theory appears complicated and hard to connect
to real systems. We synthesize results from three different kinds of models: interacting particle systems, moment
equations for spatial point processes, and metapopulation or patch models. Studies using all three frameworks
agree that spatial dynamics need not enhance coexistence nor slow down dynamics; their effects depend on the
underlying competitive interactions in the community. When similar species would coexist in a nonspatial
habitat, endogenous spatial structure inhibits coexistence and slows dynamics. When a dominant species
disperses poorly and the weaker species has higher fecundity or better dispersal, competition-colonization tradeoffs
enhance coexistence. Even when species have equal dispersal and per-generation fecundity, spatial
successional niches where the weaker and faster-growing species can rapidly exploit ephemeral local resources
can enhance coexistence. When interspecific competition is strong, spatial dynamics reduce founder control at
large scales and short dispersal becomes advantageous. We describe a series of empirical tests to detect and
distinguish among the suggested scenarios.

From ecosystems we derive food and fiber, fuel and pharmaceuticals. Ecosystems mediate
local and regional climates, stabilize soils, purify water, and in general provide
a nearly endless list of services essential to life as we know it. To understand how
to manage these services it is essential to understand how ecological communities are
organized and how to measure the biological diversity they contain. Ecological communities
are comprised of many species, which are in turn made up of large numbers of
individuals, each with their own separate ecological and evolutionary agendas. Not all
species are equal as regards their role in maintaining the functioning of ecosystems or
their resiliency in the face of stress. This chapter explains how ecosystems evolve and
function as complex adaptive systems. It examines ecological systems at scales from the
small to the large, from the individual to the collective to the community, from the leaf
to the plant to the biosphere (including the global carbon cycle). It reviews theoretical
and empirical models of ecosystem dynamics, which are highly nonlinear and contain
the potential for qualitative and irreversible shifts. It considers applications to forests,
fisheries, grasslands, and freshwater lakes.

﻿We live in an uncertain world, in which action and prudence must be continually juggled.
Caution can be costly, but indifference to serious risks can be disastrous. In all aspects of life,
we weigh risks and benefits, invoking measures to insure against events that threaten what is
most important to us, while gambling with those that can be tolerated. In matters of our
environment, science has the responsibility to inform these decisions, and society must find ways
to identify the appropriate level of circumspection. By any calculation, we must protect
ourselves against a wide variety of events that individually have low probabilities of occurrence,
and still feel good when they have not occurred. We must rely on environmental science to alert
us to an even wider set of possible disasters, many of very low probability, so that we as citizens
can decide which cause us most worry, and which mandate action.

The idea that the response of an organism to components of its physical environment, as distinct
from the availability of resources, is an important component of its niche. Differences between
species in their environmental niches may promote their coexistence. The coexistence
mechanism involved is the storage effect, augmented in the case of spatial variation by fitness
density covariance. Environmental niches are temporal niches if they refer to temporally varying
aspects of the physical environment, or spatial niches if they refer to spatially varying aspects of
the physical environment, or spatio-temporal niches, if they refer simultaneously to variation in
both space and time.

By definition, a population is regulated if it persists for many generations
with fluctuations bounded above zero with high probability. Regulation thus requires density-
dependent negative feedback whereby the population has a propensity to increase when
small and decrease when large. Ultimately, extinction occurs due to regulating mechanisms
becoming weaker than various disruptive events and stochastic variation. Population regulation
is one of the foundational concepts of ecology, yet this paradigm has often been
challenged, during the first half of the 20th century when the concept was not clearly
defined, and more recently by some who study demographically open populations.
The history of ecology reveals that earlier manifestations of the concept focused mostly
on competition as the mechanism of population regulation. Because competition is often
not evident in nature, it was sometimes concluded that population regulation was therefore
also absent. However, predation in the broadest sense can also cause density dependence.
By the 1950s, the idea that demographic density dependence was essential (but not sufficient)
for population regulation was well established, and since then, challenges to the
general concept have been short lived. However, some now believe that metapopulations
composed of demographically open local populations can persist without density dependence.
In particular, some recent manifestations of the Recruitment Limitation Hypothesis
all but preclude the possibility of regulation.
The theory of locally open populations indicates that persistence always relies on direct
demographic density dependence at some spatial and temporal scale, even in models reportedly
demonstrating the contrary. There is also increasing empirical evidence, especially
in marine systems where competition for space is not self evident, that local density dependence
is more pervasive than previously assumed and is often caused by predation.
However, there are currently insufficient data to test unequivocally whether or not any
persistent metapopulation is regulated. The challenge for more complete understanding of
regulation of metapopulations lies in combined empirical and theoretical studies that bridge
the gap between smaller scale field experiments and larger scale phenomena that can presently
be explored solely by theory.

Does biodiversity influence how ecosystems function? Might diversity loss affect the
ability of ecosystems to deliver services of benefit to humankind? Ecosystems provide
food, fuel, fiber, and drinkable water, regulate local and regional climate, and recycle
needed nutrients, among other things. An ecosystem's ability to sustain functioning may
depend on the number of species residing in the ecosystem--its biological diversity--but
this has been a controversial hypothesis. There are many unanswered questions about
how and why changes in biodiversity could alter ecosystem functioning. This volume,
written by top researchers, synthesizes empirical studies on the relationship between
biodiversity and ecosystem functioning and extends that knowledge using a novel and
coordinated set of models and theoretical approaches.
These experimental and theoretical analyses demonstrate that functioning usually
increases with biodiversity, but also reveals when and under what circumstances other
relationships between biodiversity and ecosystem functioning might occur. It also
accounts for apparent changes in diversity-functioning relationships that emerge over
time in disturbed ecosystems, thereby addressing a major controversy in the field. The
volume concludes with a blueprint for moving beyond small-scale studies to regional
ones--a move of enormous significance for policy and conservation but one that will
entail tackling some of the most fundamental challenges in ecology.
In addition to the editors, the contributors are Juan Armesto, Claudia Neuhauser, Andy
Hector, Clarence Lehman, Peter Kareiva, Sharon Lawler, Peter Chesson, Teri Balser,
Mary K. Firestone, Robert Holt, Michel Loreau, Johannes Knops, David Wedin, Peter
Reich, Shahid Naeem, Bernhard Schmid, Jasmin Joshi, and Felix Schläpfer.

Does biodiversity influence how ecosystems function? Might diversity loss affect the
ability of ecosystems to deliver services of benefit to humankind? Ecosystems provide
food, fuel, fiber, and drinkable water, regulate local and regional climate, and recycle
needed nutrients, among other things. An ecosyste's ability to sustain functioning may
depend on the number of species residing in the ecosystem--its biological diversity--but
this has been a controversial hypothesis. There are many unanswered questions about
how and why changes in biodiversity could alter ecosystem functioning. This volume,
written by top researchers, synthesizes empirical studies on the relationship between
biodiversity and ecosystem functioning and extends that knowledge using a novel and
coordinated set of models and theoretical approaches.
These experimental and theoretical analyses demonstrate that functioning usually
increases with biodiversity, but also reveals when and under what circumstances other
relationships between biodiversity and ecosystem functioning might occur. It also
accounts for apparent changes in diversity-functioning relationships that emerge over
time in disturbed ecosystems, thereby addressing a major controversy in the field. The
volume concludes with a blueprint for moving beyond small-scale studies to regional
ones--a move of enormous significance for policy and conservation but one that will
entail tackling some of the most fundamental challenges in ecology.
In addition to the editors, the contributors are Juan Armesto, Claudia Neuhauser, Andy
Hector, Clarence Lehman, Peter Kareiva, Sharon Lawler, Peter Chesson, Teri Balser,
Mary K. Firestone, Robert Holt, Michel Loreau, Johannes Knops, David Wedin, Peter
Reich, Shahid Naeem, Bernhard Schmid, Jasmin Joshi, and Felix Schläpfer.

Does biodiversity influence how ecosystems function? Might diversity loss affect the
ability of ecosystems to deliver services of benefit to humankind? Ecosystems provide
food, fuel, fiber, and drinkable water, regulate local and regional climate, and recycle
needed nutrients, among other things. An ecosyste's ability to sustain functioning may
depend on the number of species residing in the ecosystem--its biological diversity--but
this has been a controversial hypothesis. There are many unanswered questions about
how and why changes in biodiversity could alter ecosystem functioning. This volume,
written by top researchers, synthesizes empirical studies on the relationship between
biodiversity and ecosystem functioning and extends that knowledge using a novel and
coordinated set of models and theoretical approaches.
These experimental and theoretical analyses demonstrate that functioning usually
increases with biodiversity, but also reveals when and under what circumstances other
relationships between biodiversity and ecosystem functioning might occur. It also
accounts for apparent changes in diversity-functioning relationships that emerge over
time in disturbed ecosystems, thereby addressing a major controversy in the field. The
volume concludes with a blueprint for moving beyond small-scale studies to regional
ones--a move of enormous significance for policy and conservation but one that will
entail tackling some of the most fundamental challenges in ecology.
In addition to the editors, the contributors are Juan Armesto, Claudia Neuhauser, Andy
Hector, Clarence Lehman, Peter Kareiva, Sharon Lawler, Peter Chesson, Teri Balser,
Mary K. Firestone, Robert Holt, Michel Loreau, Johannes Knops, David Wedin, Peter
Reich, Shahid Naeem, Bernhard Schmid, Jasmin Joshi, and Felix Schläpfer.

A crucial unresolved problem about geological sequestration is that some
receptor reservoirs will leak stored CO2. At local scales, leaks might endanger shallower
drinking water supplies or public health. At global scales, leaks might be large enough to
make sequestration ineffective. This paper focuses on the global-scale problem and uses
models of carbon storage reservoirs and natural carbon sinks to calculate constraints on
reservoir leakage. It assumes fossil fuel consumption at a level that would that would
lead to an atmospheric CO2 concentration of 750 ppm and then calculates the
sequestration and leakage limits that would reduce the maximum concentration to 450 or
550 ppm. The surprising result is that leakage limits are much less severe than expected
because of heterogeneity among reservoirs. In some cases, the reduction from 750 to 450
ppm would be possible even with a mean leakage rate of 1% per year or more. The
results imply that economic considerations or local risks are likely to constrain allowable
leakage rates more tightly than impacts of leakage on global atmospheric CO2.

Stochastic spatial models are becoming an increasingly popular tool for
understanding ecological and epidemiological problems. However, due to the
complexities inherent in such models, it has been difficult to obtain any analytical
insights. Here, we consider individual-based, stochastic models of both the continuous time
Lotka-Volterra system and the discrete-time Nicholson-Bailey model. The stability
of these two stochastic models of natural enemies is assessed by constructing moment
equations. The inclusion of these moments, which mimic the effects of spatial
aggregation, can produce either stabilizing or destabilizing influences on the population
dynamics. Throughout, the theoretical results are compared to numerical models for the
full distribution of populations, as well as stochastic simulations.

The problem of scale has been a critical impediment to incorporating important
fine-scale processes into global ecosystem models. Our knowledge of fine-scale
physiological and ecological processes comes from a variety of measurements, ranging
from forest plot inventories to remote sensing, made at spatial resolutions considerably
smaller than the large scale at which global ecosystem models are defined. In this paper,
we describe a new individual-based, terrestrial biosphere model, which we label the ecosystem
demography model (ED). We then introduce a general method for scaling stochastic
individual-based models of ecosystem dynamics (gap models) such as ED to large scales.
The method accounts for the fine-scale spatial heterogeneity within an ecosystem caused
by stochastic disturbance events, operating at scales down to individual canopy-tree-sized
gaps. By conditioning appropriately on the occurrence of these events, we derive a size and
age-structured (SAS) approximation for the first moment of the stochastic ecosystem
model. With this approximation, it is possible to make predictions about the large scales
of interest from a description of the fine-scale physiological and population-dynamic processes
without simulating the fate of every plant individually. We use the SAS approximation
to implement our individual-based biosphere model over South America from 15°
N to 15° S, showing that the SAS equations are accurate across a range of environmental
conditions and resulting ecosystem types. We then compare the predictions of the biosphere
model to regional data and to intensive data at specific sites. Analysis of the model at these
sites illustrates the importance of fine-scale heterogeneity in governing large-scale ecosystem
function, showing how population and community-level processes influence ecosystem
composition and structure, patterns of above ground carbon accumulation, and net
ecosystem production.

Here we examine the cause, size and future of the U.S. carbon sink.
To estimate the size of the U.S. carbon sink we review a comprehensive land-based
analysis of the carbon sink in the coterminous U.S. For the 1980s, the
sink is between 1/3 and 2/3 PgC y-1, and is split approximately evenly between
forest and non-forest sectors. The non-forest sink is caused by fire suppression
on non-forested lands, sediment burial in reservoirs, alluvium and colluvium,
and agricultural practices.
The forest sink has been attributed to changes in land use and the
enhancement of plant growth by CO2 fertilization, N deposition and climate
change. To estimate the relative contribution of land use and growth enhancement
in forest ecosystems, we use forest inventory data from five states spanning a
latitudinal gradient in the eastern U.S. Land use is the dominant factor
governing the rate of carbon accumulation in forests in these states, with
growth enhancement contributing far less than previously reported. The
estimated fraction of above-ground net ecosystem production due to growth
enhancement is 2.0 ± – 4.4%, with the remainder due to land use.
To forecast the future of the U.S. carbon sink, we used the Ecosystem
Demography Model (ED). We first modeled carbon sources and sinks from
1700–1990, and then projected patterns to 2100. Our projections indicate that
the land-use portion of the U.S. carbon sink will decrease in the future, with a
half-life of approximately 50 years, as U.S. ecosystems gradually equilibrate
with current patterns of natural and anthropogenic disturbance.
Inventories of terrestrial carbon storage in the coterminous United States
(the U.S. minus Alaska and Hawaii) appear to support the conclusion that the sink
is small (4). However, inventories in the Northern Hemisphere have been able to
account for only a third or less of the 1–2 PgC y-1 indicated strongly by other lines
of evidence (5). Moreover, the two primary groups of U.S. inventory studies
strongly disagree about cause of the U.S. sink. Houghton and his colleagues (6)
used historical records of land use change, timber production, soil conservation,
wildfire rates, and simple models of carbon gains and losses in vegetation, soils
and wood products. They estimated a sink for the coterminous U.S. averaging
0.39 PgC y-1 from 1950–1990, and caused primarily by increases in crop
productivity and changes in the management of agricultural soils (0.15 PgC), and
by fire suppression on non-forested land (0.13 Pg C). They concluded that the
entire forest sector contributed only 0.07–0.12 PgC y-1.
The U.S. Forest Service (USFS) estimated a coterminous U.S. sink averaging
0.33 PgC y–1 from 1952–1992, using census and tree measurement data from the
over 100,000 plots in their Forest Inventory and Analysis (FIA) network, together
with models of soil carbon and the fate of wood products (7). Although 0.33 Pg
is close to 0.39 Pg, the entire USFS estimate is for the forest sector. If all of the
carbon identified in both (6) and (7) were real, then the annual sink for the
coterminous U.S. would be 0.60–0.65 PgC (0.33 from (7) plus 0.39 from (6)
minus the forest sector estimates from (6)) and thus the overlap between the two
estimates is only 11–20% of the total (0.07/0.65 to 0.12/0.60).
The FIA data base shows that the increase of carbon in trees has remained
remarkably steady from 1952 to 1992, at approximately 0.10 + 0.02 PgC y-1,
because regrowth in the eastern half of the U.S. consistently exceeds harvest by
about 0.1 PgC (7). This value is approximately double the increase in living forest
carbon modeled in (6). To first order, differences among published inventories
based on FIA data are caused by differences in the modeling of all forms of dead
organic matter (including slash, wood products, standing dead trees, and soil
carbon). For example, one study produced an estimate of only 0.08 PgC y-1 for
the 1980’s, because its modeling assumptions led to negligible accumulation of
nonliving carbon (8). In contrast, the assumptions behind the USFS estimate of
0.33 PgC y-1 implied that soil carbon accumulated twice as fast as living carbon
in trees. In addition, no comprehensive inventory has as yet included the carbon
sink caused by sediment burial in reservoirs, alluvium and colluvium and by the
transport of carbon into the oceans by rivers. At least one study suggests that
sediment burial and river transport may be significant (9). Finally, no
comprehensive inventory accounts for net export of carbon in agricultural and
wood products.
Ecosystem models provide the final source of information about the terrestrial
carbon sink and generally produce small estimates for the coterminous U.S. For
example, the models in the recently published VEMAP comparison produced
estimates of 0.08 + 0.02 PgC y-1 for the period from 1980–1993 (10). However,
none of these models includes the land use changes (i.e. agricultural abandonment,
fire suppression, forest harvesting and regrowth, no-till agriculture) that play such a dominant role in the inventory analyses. The models focus instead on the
effects of climate change and CO2 and nitrogen fertilization.
In what follows, we first summarize the results of a new inventory-based
analysis of the coterminous U.S. carbon sink, which shows that the sink averages
between one third and two thirds Pg annually (11). These estimates and smaller
than the 0.81–0.84 PgC y-1 in the controversial study (2) (see 11 for a discussion
of the portion of estimates in (2) that correspond to the coterminous U.S.).
However, they are significantly larger than the previously published range (one
tenth to one third PgC y-1). The analysis in (11) shows that approximately half the
sink can be unambiguously ascribed to land use and management. We then
summarize a recently published analysis (12) of the FIA data showing that the
other half of the U.S. carbon sink is also overwhelmingly caused by land use and
management.
Given that human land use rather than CO2 or nitrogen fertilization or
climate change causes the sink, it is interesting to consider the sink’s future. We
then turn to two additional studies. The first (13), introduces a new model that
incorporates the sub grid-scale heterogeneity necessary to simulate land use. The
second (14), applies this model for the past 300 years of land use in the
coterminous U.S., and shows that the U.S. sink will decrease throughout the
coming century. Unlike sinks caused by fertilization or climate change that might
increase, the land use sink will decrease as U.S. ecosystems adjust to the altered
disturbance regimes created by land use and management.

For the period 1980-89, we estimate a carbon sink in the coterminous United
States between 0.30 and 0.58 petagrams of carbon per year (petagrams of
carbon = 1015 grams of carbon). The net carbon ßux from the atmosphere to
the land was higher, 0.37 to 0.71 petagrams of carbon per year, because a net
ßux of 0.07 to 0.13 petagrams of carbon per year was exported by rivers and
commerce and returned to the atmosphere elsewhere. These land-based estimates
are larger than those from previous studies (0.08 to 0.35 petagrams of
carbon per year) because of the inclusion of additional processes and revised
estimates of some component fluxes. Although component estimates are uncertain,
about one-half of the total is outside the forest sector. We also
estimated the sink using atmospheric models and the atmospheric concentration
of carbon dioxide (the tracer-transport inversion method). The range of
results from the atmosphere-based inversions contains the land-based estimates.
Atmosphere- and land-based estimates are thus consistent, within the
large ranges of uncertainty for both methods. Atmosphere-based results for
1980-89 are similar to those for 1985-89 and 1990-94, indicating a relatively
stable U.S. sink throughout the period.

By integrating a wide range of experimental, comparative, and theoretical approaches, ecologists are
starting to gain a detailed understanding of the long-term dynamics of vegetation. We explore how
patterns of variation in demographic traits among species have provided insight into the processes
that structure plant communities. We find a common set of mechanisms, derived from ecological and
evolutionary principles, that underlie the main forces shaping systems as diverse as annual plant
communities and tropical forests. Trait variation between species maintains diversity and has
important implications for ecosystem processes. Hence, greater understanding of how Earth’s
vegetation functions will likely require integration of ecosystem science with ideas from plant
evolutionary, population, and community ecology.

Knowledge of carbon exchange between the atmosphere, land and the oceans is important, given that the terrestrial and marine
environments are currently absorbing about half of the carbon dioxide that is emitted by fossil-fuel combustion. This carbon
uptake is therefore limiting the extent of atmospheric and climatic change, but its long-term nature remains uncertain. Here we
provide an overview of the current state of knowledge of global and regional patterns of carbon exchange by terrestrial
ecosystems. Atmospheric carbon dioxide and oxygen data confirm that the terrestrial biosphere was largely neutral with respect to
net carbon exchange during the 1980s, but became a net carbon sink in the 1990s. This recent sink can be largely attributed to
northern extratropical areas, and is roughly split between North America and Eurasia. Tropical land areas, however, were
approximately in balance with respect to carbon exchange, implying a carbon sink that offset emissions due to tropical
deforestation. The evolution of the terrestrial carbon sink is largely the result of changes in land use over time, such as regrowth on
abandoned agricultural land and fire prevention, in addition to responses to environmental changes, such as longer growing
seasons, and fertilization by carbon dioxide and nitrogen. Nevertheless, there remain considerable uncertainties as to the
magnitude of the sink in different regions and the contribution of different processes.

Almost all models of plant resource limitation are grounded in either one or both of two simple conceptual models: Liebig's Minimum Hypothesis (LMH) - the idea that plants are limited by the resource in shortest supply, and the Multiple Limitation Hypothesis (MLH) - the idea that plants should adjust to their environment so that all essential resources are equally limiting. Despite the differences in their predictions, experiments have so far failed to discriminate between them. In a simple factorial nitrogen and water addition experiment in a Minnesota grassland, we observed shifts in allocation that, as in previous studies, are not all explained by a single theory. We found leaf biomass responded positively to nitrogen additions but did not respond to water additions. We found fine-root biomass increased in response to water additions, but only at low nitrogen levels and that fine-root biomass decreased in response to nitrogen additions, but only at high water levels.
To understand these responses we built a physiologically-based model of plant competition for water, nitrogen, and space to predict plant allocation to fine roots and leaves. Critically, we include in our model the inherent variability of soil moisture and treat light, water, and nitrogen as resources with distinct mechanistic roles. Experimental results showed that plants were nitrogen- and water- limited. The model explains the experimental results, under conditions of co-limitation, as follows. Foliage increases with nitrogen additions but not water additions because leaf construction is constrained by nitrogen uptake. When water is added, plants spend a larger fraction of the growing season limited by light (and effectively nitrogen) than by water. Thus, water additions cause fine-root biomass to increase because of the increased importance of nitrogen limitation. The response of fine-root biomass to water additions decreases with nitrogen additions because these additions reduce nitrogen limitation. In general, our results are explained by sequential resource limitation. The rate of carbon assimilation may be limited by a single resource at any one moment, but the identity of the limiting resource(s) changes throughout the growing season.

Almost all models of plant resource limitation are grounded in either one or both of two simple conceptual models: Liebig's Minimum Hypothesis (LMH) - the idea that plants are limited by the resource in shortest supply, and the Multiple Limitation Hypothesis (MLH) - the idea that plants should adjust to their environment so that all essential resources are equally limiting. Despite the differences in their predictions, experiments have so far failed to discriminate between them. In a simple factorial nitrogen and water addition experiment in a Minnesota grassland, we observed shifts in allocation that, as in previous studies, are not all explained by a single theory. We found leaf biomass responded positively to nitrogen additions but did not respond to water additions. We found fine-root biomass increased in response to water additions, but only at low nitrogen levels and that fine-root biomass decreased in response to nitrogen additions, but only at high water levels.
To understand these responses we built a physiologically-based model of plant competition for water, nitrogen, and space to predict plant allocation to fine roots and leaves. Critically, we include in our model the inherent variability of soil moisture and treat light, water, and nitrogen as resources with distinct mechanistic roles. Experimental results showed that plants were nitrogen- and water- limited. The model explains the experimental results, under conditions of co-limitation, as follows. Foliage increases with nitrogen additions but not water additions because leaf construction is constrained by nitrogen uptake. When water is added, plants spend a larger fraction of the growing season limited by light (and effectively nitrogen) than by water. Thus, water additions cause fine-root biomass to increase because of the increased importance of nitrogen limitation. The response of fine-root biomass to water additions decreases with nitrogen additions because these additions reduce nitrogen limitation. In general, our results are explained by sequential resource limitation. The rate of carbon assimilation may be limited by a single resource at any one moment, but the identity of the limiting resource(s) changes throughout the growing season.

Atmospheric and ground-based methods agree on the presence of a carbon sink in the
coterminous United States (the United States minus Alaska and Hawaii), and the primary
causes for the sink recently have been identified. Projecting the future behavior of the sink
is necessary for projecting future net emissions. Here we use two models, the Ecosystem
Demography model and a second simpler empirically based model (Miami Land Use History),
to estimate the spatio-temporal patterns of ecosystem carbon stocks and fluxes resulting
from land-use changes and fire suppression from 1700 to 2100. Our results are compared
with other historical reconstructions of ecosystem carbon fluxes and to a detailed carbon
budget for the 1980s. Our projections indicate that the ecosystem recovery processes that
are primarily responsible for the contemporary U.S. carbon sink will slow over the next
century, resulting in a significant reduction of the sink. The projected rate of decrease
depends strongly on scenarios of future land use and the long-term effectiveness of fire
suppression.